Comments (3)
I have effectively the same question: how could you resample in an iterative fashion such that you could process signals that are larger than the available system memory?
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In principle, you could do this by buffering your large signal into overlapping windows, resampling the windows, and then overlap-adding the results. None of this should be conceptually difficult to do -- the stride between windows can be set to match the length of the interpolation filter -- but it would take a little bit of care to do efficiently and without distortion.
If anyone is serious about implementing this, it would be great to have. I won't have the time to do it myself for the near future though.
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Closing this out - see #67 for a bit more discussion on the topic.
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Related Issues (20)
- v0.3.0 produces other results than v0.2.2 HOT 3
- Resampy 0.3.0 is slow for multi-dimensional input HOT 5
- Issues with Numba 0.55.2 HOT 4
- Resampy 0.3.1 slows down other libraries HOT 43
- Use parallel=True by default can be problematic in multiprocessing applications HOT 8
- Bringing import time back down
- Edge Case, rounding error in length calculation HOT 3
- Missing argument in guvectorize decorator ? HOT 2
- Quality issues? HOT 5
- resampling to the same hz HOT 1
- Incompatible with latest numba HOT 3
- Best quality resampling?
- PyPI status HOT 2
- Add linting CI
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- Fix documentation builds HOT 1
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